What you should know

- [Instructor] To get the most out of this course,it helps to be familiar with Python Three specifically.However, experienced Python 2.7 developersshould have no problem following the course.Additionally, some command line familiaritywith help for running scripts.Note that you do not need any prior OpenCVor other image processing experiencein order to be successful at this course.In terms of software, I'll be showing youfull installation process for OpenCV 3.2 and Python 3.6.Specifically for Windows, Mac OS X,and Ubuntu Linux.

If you have older versions of OpenCV and Python,you should be able to follow along,but I would recommend following these stepsto install OpenCV 3.2 and Python 3.6.Finally, while I'll be using Sublime Text,any text editing software will work.

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Released

9/22/2017

OpenCV is an open-source toolkit for advanced computer vision. It is one of the most popular tools for facial recognition, used in a wide variety of security, marketing, and photography applications, and it powers a lot of cutting-edge tech, including augmented reality and robotics. This course offers Python developers a detailed introduction to OpenCV 3, starting with installing and configuring your Mac, Windows, or Linux development environment along with Python 3. Learn about the data and image types unique to OpenCV, and find out how to manipulate pixels and images. Instructor Patrick W. Crawford also shows how to read video streams as inputs, and create custom real-time video interfaces. Then comes the real power of OpenCV: object, facial, and feature detection. Learn how to leverage the image-processing power of OpenCV using methods like template matching and machine learning data to identify and recognize features.